Publication
Dynamic Opacity Optimization for Scatter Plots
Abstract
Scatterplots are an effective and commonly used technique to show the relationship between two variables. However, as the number of data points increases, the chart suffers from “over-plotting” which obscures data points and makes the underlying distribution of the data difficult to discern. Reducing the opacity of the data points is an effective way to address over-plotting, however, setting the individual point opacity is a manual task performed by the chart designer. We present a user-driven model of opacity scaling for scatter plots. We built our model based on crowd-sourced responses to opacity scaling tasks using several synthetic data distributions, and then test our model on a collection of real-world data sets.
Download publicationRelated Resources
See what’s new.
2025
An online-adaptive hyperreduced reduced basis element method for parameterized component-based nonlinear systems using hierarchical error estimationPresents an online-adaptive, hyperreduced reduced basis element method…
2024
Exploring Opportunities for Adopting Generative AI in Automotive Conceptual DesignThis research discusses opportunities for adopting generative AI in…
2023
Language Model Crossover: Variation through Few-Shot PromptingPursuing the insight that language models naturally enable an…
2019
Design Loop: Calibration of a Simulation of Productive Congestion Through Real-World Data for Generative Design FrameworksThis paper extends the applicability of generative design for space…
Get in touch
Something pique your interest? Get in touch if you’d like to learn more about Autodesk Research, our projects, people, and potential collaboration opportunities.
Contact us